Many companies and other organizations operate computer networks that interconnect numerous computing systems to support their operations, such as with the computing systems being co-located (e.g., as part of a local network) or instead located in multiple distinct geographical locations (e.g., connected via one or more private or public intermediate networks). For example, data centers housing significant numbers of interconnected computing systems have become commonplace, such as private data centers that are operated by and on behalf of a single organization, and public data centers that are operated by entities as businesses to provide computing resources and services to customers. Some public data center operators provide network access, power, and secure installation facilities for hardware owned by various customers, while other public data center operators provide “full service” facilities that also include hardware resources made available for use by their customers. However, as the scale and scope of typical data centers has increased, the tasks of provisioning, administering, and managing the physical computing resources have become increasingly complicated.
The advent of virtualization technologies for commodity hardware has provided benefits with respect to managing large-scale computing resources for many customers with diverse service needs, allowing various computing resources and services to be efficiently and securely shared by multiple customers. For example, virtualization technologies may allow a single physical computing machine to be shared among multiple users by providing each user with one or more virtual machines hosted by the single physical computing machine, with each such virtual machine being a software simulation acting as a distinct logical computing system that provides users with the illusion that they are the sole operators and administrators of a given hardware computing resource, while also providing application isolation and security among the various virtual machines. Furthermore, some virtualization technologies are capable of providing virtual resources that span two or more physical resources, such as a single virtual machine with multiple virtual processors that spans multiple distinct physical computing systems. As another example, virtualization technologies may allow data storage hardware to be shared among multiple users by providing each user with a virtualized data store which may be distributed across multiple data storage devices, with each such virtualized data store acting as a distinct logical data store that provides users with the illusion that they are the sole operators and administrators of the data storage resource.
In many environments, various types of distributed applications may be implemented using virtualized compute and storage resources that may span numerous devices. For example, some provider network operators may be able to provision clusters of virtual compute instances suitable for high-performance applications that may potentially require high bandwidth interconnections between the nodes of the cluster, where each node includes high-end processing cores. In other examples, collections of virtual compute and storage nodes may be combined in various ways to implement general-purpose or special-purpose database systems. Different resources within the collection may have different roles in the distributed application; e.g., some resources may have supervisory roles over other resources, others may have worker roles that have tasks assigned to them by the supervisors, and so on. Traditionally, at least in some provider networks, the bandwidth usage limits for various types of resources have been set by the operators without an awareness of the roles played by the resources within their distributed applications, e.g., all compute resources of a certain compute capability may be assigned the same bandwidth usage limits. Such application-unaware bandwidth usage limits can potentially lead to undesirable results, such as oversubscription scenarios in which the provider network operator cannot provide the promised bandwidth to all the resources simultaneously, ultimately resulting in lowered client satisfaction levels.
While embodiments are described herein by way of example for several embodiments and illustrative drawings, those skilled in the art will recognize that embodiments are not limited to the embodiments or drawings described. It should be understood, that the drawings and detailed description thereto are not intended to limit embodiments to the particular form disclosed, but on the contrary, the intention is to cover all modifications, equivalents and alternatives falling within the spirit and scope as defined by the appended claims. The headings used herein are for organizational purposes only and are not meant to be used to limit the scope of the description or the claims. As used throughout this application, the word “may” is used in a permissive sense (i.e., meaning having the potential to), rather than the mandatory sense (i.e., meaning must). Similarly, the words “include,” “including,” and “includes” mean including, but not limited to.